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I have trained a model with atomic as the label, the function get_batch doesn't return the shape of my original data when I use evaluate.py, how can I solve this please?
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Hi All ,
Wanted to understand , when we evaluate using the plot_decision_boundary. But how do we test the model apart from it.
Do we give the new test values to the model and then plot it again…
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### Describe your problem
Is it possible to integrate Ragas into RagFlow for model evaluation? Any idea would be welcome
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Hey @Ahmedest61, it was great meeting you at ECCV!
Are there any plans to release the trained model on torch.hub? It is quite simple to do and allows people to use your model with two lines of code…
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Hello Author!
I apologize for the intrusion. I wanted to ask about using the point2rbox-v2 model. Following your suggestion to reduce the learning rate on a single GPU, I still haven't achieved acc…
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I propose adding an e-commerce sales prediction model to ML Nexus. This model will utilize historical sales data, marketing spend, customer behavior, and seasonal trends to forecast future sales. It w…
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Thx for your amazing work! I also notice that you haven't provided the **Pretrained model & Evaluation code**. Is there any possible that you would upload them?
Thanks again!
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# Paper Information
- **Paper Title**: MeanSparse: Post-Training Robustness Enhancement Through Mean-Centered Feature Sparsification
- **Paper URL**: https://arxiv.org/pdf/2406.05927
- **Paper au…
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How do you evaluate the model? The generated images from synthetic data and real data are difficult to differentiate.
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- Confusion Matrix
- Classification Report (sklearn)
But this will likely be migrated to a separate notebook